MRI in soils: determination of water concent changes due to root water uptake by means of a multi-slice-multi-echo sequence (MSME)

Root water uptake by ricinus communis (castor bean) in fine sand was investigated using MRI with multiecho sampling. Before starting the experiments the plants germinated and grew for 3 weeks in a cylindrical container with a diameter of 9 cm. Immediately before the MRI experiments started, the containers were water-saturated and sealed, so water content changes were only caused by root water uptake. In continuation of a preceding work, where we applied SPRITE we tested a multi-echo multi-slice sequence (MSME). In this approach, the water content was imaged by setting TE = 6.76 ms and nE = 128 with an isotropic resolution of 3.1mm. We calculated the water content maps by biexponential fitting of the multi-slice echo train data and normalisation on reference cuvettes filled with glass beads and 1 mM NiCl2 solution. The water content determination was validated by comparing to mean gravimetric water content measurements. By coregistration with the root architecture, visualised by a 3D fast spin echo sequence (RARE), we conclude that the largest water content changes occurred in the neighbourhood of the roots and in the upper layers of the soil

Stochastic Continuum Transport Equations for Field-Scale Solute Transport: Overview of Theoretical and Experimental Results

One-dimensional transport models that predict field-scale averaged solute fluxes are often used to estimate the risk of nonpoint source groundwater contamination by widespread surface-applied chemicals. However, within-field variability of soil hydraulic properties leads to lateral variation in local solute fluxes. When this smaller scale variability is characterized in a geostatistical sense, stochastic three-dimensional flow and transport equations can be used to predict field-scale averaged transport in terms of geostatistical parameters. We discuss the use of stochastic equations for the parameterization of equivalent one-dimensional models predicting averaged solute fluxes. First, we consider the equivalent one-dimensional convection dispersion model and the equivalent dispersivity, which characterizes the spreading of laterally averaged concentrations or solute fluxes. Second, we discuss the parameterization of a stream tube model to predict local transport variables (i.e., distributions of local concentrations and local arrival times) These local transport variables are shown to be important for predicting nonlinear local transport processes and useful for inversely inferring the spatial structure of soil properties. Stochastic flow and transport equations reveal a dependency of equivalent model parameters on transport distance and flow rate, which reflects the importance of smaller scale heterogeneities on field-scale transport. Approximate solutions of stochastic flow and transport equations are obtained for steady-state and uniform flow. The effect of transient flow conditions on transport is discussed. Throughout the paper we refer to experimental and numerical data that confirm or contradict results from stochastic flow and transport equations

On the information content of incubation studies

The measurement of the production of CO2 from soils in incubation studies has been used for many years to gain information about the influence of different soils types, changing temperatures and water contents, as well as the addition of amendments on the soil respiration. While in the early years the kinetic modelling (or fitting) was restricted to the single or one pool model due to the possibility of solving the problem by log-transforming the observed data an using a linear regression for the estimation of the rate constant (by doing so an analytical solution can be applied), more recent publications chose multi-pool models (2, 3, and even 4-pools), which can will be fitted iteratively using appropriate computer software. In general, there are different methods used in literature to estimate the kinetic parameters resulting in different kinetic parameter values even for the same data set. Additionally, screening of existing literature revealed that the 2-pool model (or even higher pool models) were sometimes obviously wrong fitted or over fitted. In our presentation, we will show how different constrains in the fitting process will influence the results of the kinetic parameter values, how obviously wrong fitting and overfitting can be easily detected, and how the information content of the incubation data can be easily judged prior any fitting. Finally, we will provide recommendations how to extract information from incubation experiments